Take control of your data – and free up IT – with self-service data preparation.
Manage data – no special skills needed.
Perform data integration, data quality and data preparation tasks yourself, without having to write code or ask for specialized help. SAS Data Loader for Hadoop bridges the skills gap, giving all users access to their data regardless of technical ability.
Boost scalability and performance.
Business users find it easy to use. Data scientists and SAS coders like its speed, efficiency and agility. A code accelerator harnesses the power of Hadoop, and data quality functions run in memory on Spark for better performance. And by minimizing data movement, you increase your data's security.
Ensure big data quality.
Take control of the data within data lake environments. SAS Data Loader for Hadoop allows you to profile data to understand its overall quality. Then you can standardize, parse, match and perform other core data quality functions, resulting in quality data for business needs inside of the data lakes.
Speed data management processes with Spark.
Data quality functions run in memory in Apache Spark for improved performance. Matching and best record creation enables master data management for big data. In addition, you can read and write to Spark data sets as needed.
Load your data into or out of Hadoop and data lakes. Prep it so it's ready for reports, visualizations or advanced analytics – all inside the data lakes. And do it all yourself, quickly and easily.
Explore More on SAS® Data Loader for Hadoop and Beyond
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- Технический документ How Hadoop Helps Realize Big Data ValueLeveraging a big-picture approach to Hadoop opens up a world of data-fueled opportunities.
- Технический документ Eight Considerations for Utilizing Big Data Analytics with HadoopThis paper focuses on eight considerations when it comes to applying big data analytics to extract value from Hadoop. Readers will learn about the importance of in-memory analytics, how to optimize the data preparation processes and the skill sets needed to derive benefits from Hadoop.
- Технический документ Data Integration Déjà Vu: Big Data Reinvigorates DIDiscover why the latest evolution of data integration delivers more value from big data.
- Технический документ Improving Data Preparation for Business AnalyticsThis TDWI Best Practices Report discusses the latest data preparation processes, self-service options and how to effectively integrate data prep with analytics and BI solutions.
- Технический документ Understanding Big Data Quality for Maximum Information UsabilityDiscover why data quality and data governance are so important to large-scale analytics. Learn how to balance governance with usability so you can come up with a strategic plan for managing big data.
- Технический документ Recommendation SystemsIn this paper, Wayne Thompson, PhD, Manager of Data Sciences Technologies at SAS answers common questions about the types of recommendation systems used today, who uses them and why, and the advantages of using them for businesses today. He also delves into how the underlying technology typically works, with a special focus on SAS capabilities and benefits.
- Interview The scoop on HadoopCloudera co-founder Mike Olson talks trends, changes and outlines the formula for success with Hadoop.
- Технический документ Using Next-Generation Advanced Analytics to Harness Big DataDiscover why Heavy Reading recommends using advanced analytics from proven vendors to obtain real-time intelligence from all your big data.
- Технический документ Managing the Analytics Life Cycle for Decisions at ScaleLet the SAS Analytics Life Cycle guide you through the iterative process of going from raw data to predictive modeling to automated decisions, faster. This paper tells you how.
- Технический документ Self-Service Big Data Preparation in the Age of Hadoop: A Conversation with SASLearn how SAS Data Loader for Hadoop enables business users – along with data scientists and IT – to access, profile, transform and cleanse Hadoop data. The best part is, it requires minimal training and no need for coding.
- Технический документ The Current State of Hadoop in the EnterpriseWritten by the International Institute for Analytics, this paper presents a broad view of Hadoop in the marketplace, including how it is being adopted and used by global organizations. It then offers a set of recommendations that organizations can use to succeed with Hadoop.
- Технический документ SAS and the Hadoop EcosystemA vendor profile from The Bloor Group that refers to the full report: Making Sense of Hadoop and its Ecosystem.
- Технический документ Making Sense of Hadoop and its EcosystemAn Investigation into the Evolution and Deployment of Hadoop
- Технический документ Hadoop for the Enterprise: Making Data Management Massively Scalable, Agile, Feature-Rich, and Cost-EffectiveThis TDWI report accelerates users’ understanding of new products, technologies and best practices that have emerged around Hadoop. It will also help readers connect available options to use cases, with a focus on mainstream enterprise uses, while respecting proven IT practices and delivering maximum business value.
- Технический документ Best Practices for Hadoop: A Guide From SAS CustomersEase your transition to Hadoop by following these tried-and-true best practices from SAS customers.
- Технический документ Data Quality Challenges and PrioritiesFind out how organizations are addressing their most pressing data quality issues, discover the top 10 priorities for data quality solutions, and learn the best ways to engage and empower business users to improve data quality.
- Технический документ Drive Next-Generation Customer Experiences with Real-Time Connected Product and Service Analytics SAS, Hortonworks and Intel can help you embrace technologies and processes to anticipate a wide range of customer needs, providing the foundation for next-generation customer experiences.
- Технический документ A Non-Geek’s Big Data PlaybookThis paper examines how a non-geek yet technically savvy business professional can understand how to use Hadoop - and how it will impact enterprise data environments for years to come. The paper serves as a playbook that demonstrates six common “plays” that illustrate how Apache Hadoop can support and extend the enterprise data warehouse (EDW) ecosystem.
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